Table 2. Definitions of the used mathematical terms.

Name	Quantifies	Number of data sets/permutations	Description
Terms describing experimental variances
mmax or gmaxm2 or g2	Eigenvectors of most (max) and second most (2) mutational (m) and genetic (g) variance		Estimated by diagonalizing the respective M or G matrix
M26 G26	Mutational (M) or standing genetic (G) covariance among functional groups		Phenotypic scores were estimated for individuals for the trait combinations described by the first and second major axes of within-function mutational or standing genetic variance for each of the 13 functional groups (i.e., 26 traits). These scores were then analyzed as per observed traits to estimate the 26 trait variance covariance matrix, which was then diagonalized.
Terms used to build distributions used in estimating C.I.s
Mse Gse	Sampling error within the mutational (M) or standing genetic (G) data sets	50	Data shuffled among lines, disrupting the mutational or genetic covariances between traits while retaining the observed levels of variance for each individual gene expression trait
Mbb Gbb	Biological background levels of mutational (M) or standing genetic (G) covariance among genes for which there is no a priori expectation of functional relatedness	143	Uses random sets of genes taken from the list of genes that were not assigned to one of the 14 functional groups. Each of the 117 data sets was then subsampled to the same number of genes as in the respective functional group.
M26se G26se	Sampling error within the among functional group mutational (M26) or standing genetic (G26) covariance matrices	50	Data shuffled among lines, disrupting the mutational or genetic covariances between traits while retaining the observed levels of variance for each composite trait present in M26 and G26